Ten considerations for conservation policy makers for the post-COVID-19 transition
Bibliographic record
Abstract
Public health and safety concerns around the SARS-CoV-2 novel coronavirus and the COVID-19 pandemic have greatly changed human behaviour. Such shifts in behaviours, including travel patterns, consumerism, and energy use, are variously impacting biodiversity during the human-dominated geological epoch known as the Anthropocene. Indeed, the dramatic reduction in human mobility and activity has been termed the “Anthropause”. COVID-19 has highlighted the current environmental and biodiversity crisis and has provided an opportunity to redefine our relationship with nature. Here we share 10 considerations for conservation policy makers to support and rethink the development of impactful and effective policies in light of the COVID-19 pandemic. There are opportunities to leverage societal changes as a result of COVID-19, focus on the need for collaboration and engagement, and address lessons learned through the development of policies (including those related to public health) during the pandemic. The pandemic has had devastating impacts on humanity that should not be understated, but it is also a warning that we need to redefine our relationship with nature and restore biodiversity. The considerations presented here will support the development of robust, evidence-based, and transformative policies for biodiversity conservation in a post-COVID-19 world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".